Derivation and Validation of a Prognostic Model for Cancer Dependency Genes Based on CRISPR-Cas9 in Gastric Adenocarcinoma

• Published in: Frontiers in oncology Vol. 11; p. 617289
• Main Authors: Zhou, Wenjie, Li, Junqing, Lu, Xiaofang, Liu, Fangjie, An, Tailai, Xiao, Xing, Kuo, Zi Chong, Wu, Wenhui, He, Yulong
• Format: Journal Article
• Language: English
• Published: Switzerland Frontiers Media S.A 25.02.2021
• Subjects: Cancer Dependency Map; gastric adenocarcinoma; invasion and metastasis; Oncology; prognostic model; TCGA; Cancer Dependency Map; gastric adenocarcinoma; prognostic model; invasion and metastasis; TCGA
• ISSN: 2234-943X; 2234-943X
• DOI: 10.3389/fonc.2021.617289

As a CRISPR-Cas9-based tool to help scientists to investigate gene functions, Cancer Dependency Map genes (CDMs) include an enormous series of loss-of-function screens based on genome-scale RNAi. These genes participate in regulating survival and growth of tumor cells, which suggests their potential as novel therapeutic targets for malignant tumors. By far, studies on the roles of CDMs in gastric adenocarcinoma (GA) are scarce and only a small fraction of CDMs have been investigated. In the present study, datasets of the differentially expressed genes (DEGs) were extracted from the TCGA-based (The Cancer Genome Atlas) GEPIA database, from which differentially expressed CDMs were determined. Functions and prognostic significance of these verified CDMs were evaluated using a series of bioinformatics methods. In all, 246 differentially expressed CDMs were determined, with 147 upregulated and 99 downregulated. Ten CDMs (ALG8, ATRIP, CCT6A, CFDP1, CINP, MED18, METTL1, ORC1, TANGO6, and PWP2) were identified to be prognosis-related and subsequently a prognosis model based on these ten CDMs was constructed. In comparison with that of patients with low risk in TCGA training, testing and GSE84437 cohort, overall survival (OS) of patients with high risk was significantly worse. It was then subsequently demonstrated that for this prognostic model, area under the ROC (receiver operating characteristic) curve was 0.771 and 0.697 for TCGA training and testing cohort respectively, justifying its reliability in predicting survival of GA patients. With the ten identified CDMs, we then constructed a nomogram to generate a clinically practical model. The regulatory networks and functions of the ten CDMs were then explored, the results of which demonstrated that as the gene significantly associated with survival of GA patients and Hazard ratio (HR), PWP2 promoted invasion and migration of GA cell lines through the EMT signaling pathway. Therefore, in conclusion, the present study might help understand the prognostic significance and molecular functions of CDMs in GA.